Cl, a new tool to assess soil carbon dynamics.

Soil organic carbon is one of the largest surface pools of carbon that humans can manage in order to partially mitigate annual anthropogenic CO emissions. A significant element to assess soil sequestration potential is the carbon age, which is evaluated by modelling or experimentally using carbon isotopes. Results, however, are not consistent.

Barriers and opportunities of soil knowledge to address soil challenges: Stakeholders' perspectives across Europe.

Climate-smart sustainable management of agricultural soil is critical to improve soil health, enhance food and water security, contribute to climate change mitigation and adaptation, biodiversity preservation, and improve human health and wellbeing. The European Joint Programme for Soil (EJP SOIL) started in 2020 with the aim to significantly improve soil management knowledge and create a sustainable and integrated European soil research system. EJP SOIL involves more than 350 scientists across 24 Countries and has been addressing multiple aspects associated with soil management across different European agroecosystems.

CATH: increased structural coverage of functional space.

CATH (https://www.cathdb.info) identifies domains in protein structures from wwPDB and classifies these into evolutionary superfamilies, thereby providing structural and functional annotations.

Agriculture increases the bioavailability of silicon, a beneficial element for crop, in temperate soils.

Crops may take benefits from silicon (Si) uptake in soil. Plant available Si (PAS) can be affected by natural weathering processes or by anthropogenic forces such as agriculture. The soil parameters that control the pool of PAS are still poorly documented, particularly in temperate climates.

Detecting the Guttman effect with the help of ordinal correspondence analysis in synchrotron X-ray diffraction data analysis.

We propose a method for detecting a Guttman effect in a complete disjunctive table with questions. Since such an investigation is a nonsense when the variables are independent, we reuse a previous unpublished work about the chi-squared independence test for Burt's tables. Then, we introduce a two-steps method consisting in plugging the first singular vector from a preliminary Correspondence Analysis (CA) of as a score into a subsequent singly-ordered Ordinal Correspondence Analysis (OCA) of .